ARTIFICIAL DENDRITIC TREES

The electronic architecture and dynamic signal processing capabilities of an artificial dendritic tree that can be used to process and class ify dynamic signals is described. The electrical circuit architecture is modeled after neurons that have spatially extensive dendritic trees . The artificial dendritic tree is a hybrid VLSI circuit and is sensit ive to both temporal and spatial signal characteristics. It does not u se the conventional neural network concept of weights, and as such it does not use multipliers, adders, look-up-tables, microprocessors; or other complex computational units to process signals. The weights of c onventional neural networks, which take the form of numerical, resisti ve, voltage, or current values, but do not have any spatial or tempora l content, are replaced with connections whose spatial location have b oth a temporal and scaling significance.